Application of fuzzy enhancement in moving object detection and tracking

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, we propose an improved fuzzy enhancement algorithm for the moving object detection and tracking. A new membership function is proposed based on the theory of fuzzy sets, which improves the traditional Pal-King fuzzy enhancement algorithm and overcomes the loss of gray information after the processing of enhancement. Since a gray image with multiple targets need more than one crossover point (threshold) for image segmentation, a method for multi-threshold segmentation based on Otsu algorithm is proposed. This method can get multiple thresholds of the image accurately in a short time. After the processing of fuzzy enhancement the moving object is detected and tracked according to the image centroid. Experimental results show that the proposed algorithm can achieve moving object detection and tracking accurately and quickly.

Original languageEnglish
Title of host publication2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509035496
DOIs
StatePublished - 2016
Externally publishedYes
Event14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016 - Phuket, Thailand
Duration: 13 Nov 201615 Nov 2016

Publication series

Name2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016

Conference

Conference14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016
Country/TerritoryThailand
CityPhuket
Period13/11/1615/11/16

Keywords

  • crossover point
  • detection
  • fuzzy enhancement
  • membership function
  • tracking

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